S19 Respiratory health hazards in the wind industry
Bibliographic record
Abstract
<h3>Introduction</h3> The wind industry is experiencing significant growth in the UK. Production of on and offshore wind has not commonly been associated with respiratory health hazards. This scoping review aimed to understand existing evidence for respiratory health hazards associated with working in the wind industry. <h3>Methodology</h3> A scoping review was performed using predefined search terms in OVID, Web of Knowledge, EBSCO, and SCOPUS, and reported according to PRISMA methodology (figure 1). Systematic reviews were screened for additional references. Information on relevant exposures was sought from industry sources and was also included in the review. Studies were included if published in English and regarding respiratory health hazards in the wind industry. Studies were excluded if they only addressed hazards associated with manufacture of components for the wind industry. <h3>Results</h3> Nineteen articles were included. Papers published were heterogenous in terms of quality and methodology, and few directly addressed potentially harmful respiratory exposures in the wind industry. Respiratory hazards were identified during turbine maintenance and repair, including epoxy resins, isocyanates, phthalic anhydrides, silica dust, styrene, fiberglass, and particulate. One study identified a risk of offshore exposure to contaminated water associated with Legionella and another offshore study identified an associated with brevotoxin-releasing phyloplankton and exacerbations of asthma. <h3>Conclusion</h3> We identified several potential respiratory hazards associated with working in the wind industry, particularly in maintenance and repair. Biological hazards were associated with work in offshore environments. Workers, employers, and policy makers should be aware of potential hazards associated with working in wind and measures taken to mitigate any identified risks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".